measure-okr-grader

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Scores completed OKR sets at cycle close with KR-level scoring per the canonical OKR type enum (committed | aspirational | learning | operational_health | compliance_or_safety), committed-vs-aspirational interpretation, evidence quality assessment, learning synthesis, and next-cycle recommendations. Refuses to retroactively change targets or shrink committed scope, average away guardrail KRs, treat 0.7 as success for committed or compliance_or_safety KRs, equate effort with impact, or use scores for individual performance. Hands off to iterate-lessons-log, iterate-retrospective, define-hypothesis, measure-dashboard-requirements, measure-instrumentation-spec, and foundation-okr-writer.

AI & Automation 557 stars 73 forks Updated today Apache-2.0

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Quality Score: 94/100

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License 10%
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Description 5%
100

Skill Content

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # OKR Grader An OKR Cycle Review is a backward-looking artifact that closes the loop on a completed OKR set. It scores each KR against its baseline and target, separates committed from aspirational interpretation, surfaces what evidence does and does not support, names what the team learned, and prepares input for next-cycle drafting. Done well, a cycle review protects the integrity of the OKR operating system by refusing to dress up missed commitments as aspirational stretch, refusing to celebrate effort over outcome, and refusing to let scoring carry weight it cannot bear. This skill is an evidence interpreter, not an arithmetic engine. Its job is to read final KR values, compare them against the original OKR set's intent, and produce a review that names the learning honestly. It enforces the empirical scoring conventions drawn from Doerr (`Measure What Matters`), Wodtke (`Radical Focus`), Castro (committed vs aspirational interpretation), Grove (`High Output Management`), and the OKR community's accumulated practice on misuse failure modes. It pairs with `foundation-okr-writer` (which produced the OKR set being scored) and hands off the learnings produced here to the iterate skills that consume them. ## When to Use - The OKR cycle has ended (or you are scoring a partial-cycle close) - You have final or interim KR values, baselines, and targets - Stakeholders need a clear review with score...

Details

Author
product-on-purpose
Repository
product-on-purpose/pm-skills
Created
7 months ago
Last Updated
today
Language
JavaScript
License
Apache-2.0

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